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DATA SCIENCE PYTHON PLAYGROUND

Data Foundations · A little practice goes a long way.

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Optional · distribution detail · V14 · 8 MIN

Non-overlapping raw points

Separate observations without changing their values.

Exercises within this concept

  1. FollowFollow the techniqueCurrent exercise
  2. ChangeAdapt a requirement
  3. TransferCombine earlier skills

Understand the idea

A swarm plot moves points sideways just enough to reduce overlap while preserving every measured value.

Concept sketch: swarm packs equal values without overlapABswarm packs equal values without overlap
Illustration · not the exercise output

A small example

Several records measuring 4 line up beside one another at value 4; none is moved to a different measurement.

Follow the code

Apply the idea to the supplied table. Read from top to bottom; the final line displays the result.

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(figsize=(6, 4))
sns.swarmplot(data=df, x="flavour", y="price", size=5, ax=ax)
ax.set(title="Candy shop", xlabel="flavour", ylabel="price")
fig.tight_layout()
plt.show()

What each part does

sns.swarmplot
spread markers to avoid overlap
size=5
marker size, not a data mapping

Your inputs

The editable setup on the right creates df. Run executes the setup and your work from top to bottom.

Candy shop · 6 synthetic rows
candyflavourpriceratingshelf
Gummy Bearfruity1.24.1A
Choco Popchocolate2.14.6B
Mint Bitemint1.53.8A
Berry Loopfruity2.84.4B
Cocoa Cubechocolate3.44.9A
Lemon Dropfruity1.84B

Your task · Follow

  1. Using df, call sns.swarmplot with flavour on x and price on y, using size=5.
  2. Chart: title "Candy shop"; x "flavour"; y "price".
Hint

Swarm packing moves points along the category direction while retaining their measurements.

Reveal solution

One way to do it. Keep any supplied setup in the editor and use this in the Your work section.

import matplotlib.pyplot as plt
import seaborn as sns

fig, ax = plt.subplots(figsize=(6, 4))
sns.swarmplot(data=df, x="flavour", y="price", size=5, ax=ax)
ax.set(title="Candy shop", xlabel="flavour", ylabel="price")
fig.tight_layout()
plt.show()
Your task · Follow
  1. Using df, call sns.swarmplot with flavour on x and price on y, using size=5.
  2. Chart: title "Candy shop"; x "flavour"; y "price".

Tab: indent · Shift+Tab: outdent · Esc, then Tab: leave editor

Edit Python. Control or Command plus Enter runs it. Tab indents by four spaces. Shift plus Tab outdents. Press Escape, then Tab or Shift plus Tab to leave the editor.

Each run executes all editor code in a fresh Python session. Display charts with plt.show().

Python starts when you open a lesson.

Output

Run your code to see what Python returns.